In the real world, most object shapes are perspectively transformed when imaged. How to recognize or locate such shapes in images is interesting and important. The conventional generalized Hough transform (GHT) is useful for detecting or locating translated two-dimensional (2D) planar shapes. However, it cannot be used for detecting perspectively transformed planar shapes. A new version of the GHT, called perspective-transformation-invariant generalized Hough transform (PTIGHT), is proposed to remove this weakness. The PTIGHT is based on the use of a new perspective reference table that is built up by applying both forward and inverse perspective transformations on a given template shape image from all viewing directions and positions. Due to the use of the point spread function to express the perspective reference table, the required dimensionality of the Hough counting space (HCS) for the PTIGHT is reduced to 2D. After performing the PTIGHT on an input image, the peaks in the HCS whose values are larger than a threshold is picked out as the candidate locations of the perspective shape to be detected in the input images. By performing an inverse PTIGHT on the candidates, one of the candidate locations whose corresponding shape marches best with the input shape is selected and the desired parameters of the perspective transformation can be obtained. Some experimental results are included to demonstrate the applicability of the proposed PTIGHT. (C) 1997 Pattern Recognition Society.